Everybody Lies: Big Data, New Data, and What the Internet Reveals About Who We Really Are
Digital Seminar Series: Seth Stephens-Davidowitz, The New York Times & Wharton
Abstract: How much sex do people really have? Does advertising work? How many Americans are racist? Is America experiencing a hidden back-alley abortion crisis? Can you game the stock market? Does violent entertainment increase the rate of violent crime? What should you say on a first date if you want a second? What’s the best place to raise your kids? Do parents treat sons differently from daughters? What makes a story go viral? How many people actually read the books they buy? In this ground-breaking work, Seth Stephens-Davidowitz, a Harvard-trained economist, former Google data scientist, and New York Times writer, argues that much of what we thought about people has been dead wrong. The reason? People lie, to friends, lovers, doctors, surveys—and themselves. However, we no longer need to rely on what people tell us. New data from the internet — the traces of information that billions of people leave on Google, social media, dating, and even pornography sites — finally reveals the truth. By analyzing this digital goldmine, we can now learn what people really think, what they really want, and what they really do. Sometimes, the new data will make you laugh out loud. Sometimes, the new data will shock you. Sometimes, the new data will deeply disturb you. But, always, this new data will make you think. Everybody Lies combines the informed analysis of Nate Silver’s Signal and the Noise, the storytelling of Malcolm Gladwell’s Outliers, and the wit and fun of Stephen Dubner and Steven Levitt’s Freakonomics in a book that will change the way you view the world. There is almost no limit to what can be learned about human nature from Big Data — provided, that is, you ask the right questions.
You can listen to Seth’s talk here and read more about his book here
Bio: Seth Stephens-Davidowitz is a contributing op-ed writer for the New York Times, a lecturer at Wharton, and a former Google data scientist. He received a BA in philosophy from Stanford, where he graduated Phi Beta Kappa, and a PhD in economics from Harvard. His research—which uses new, big data sources to uncover hidden behaviors and attitudes—has appeared in The Journal of Public Economics and other prestigious publications. He lives in New York City.